Microclimate influences on vegetation water availability and net primary production in coastal ecosystems of Central California

Field sampling and satellite remote sensing were used to test the hypothesis that site microclimate variability leading to divergent soil water use by vegetation types is closely associated with variability in annual net primary productivity (NPP) at the landscape scale. A simulation model based on satellite observations of seasonal phenology was used to estimate NPP of grassland, shrubland, and conifer forest vegetation types on the Central California coast near Big Sur. Daily microclimate at the soil surface was monitored over 4 years (2008–2011) for each vegetation type to infer soil moisture controls on plant production. Grassland soils were found to have lower soil organic matter content and were subjected to extreme radiation and wind events, and thereby dry-down faster with daily spring–summer warming than do shrubland or redwood forest soils. This reduced moisture microclimate affected the water stress on grassland plants to reduce NPP fluxes from April to October each year on the Central Coast far sooner than for shrubland or redwood stands. Results from this study suggested that the satellite-observed canopy greenness variations represented can be used to quantify plant production in coastal ecosystems at the landscape scale of defined microclimate variation.     

What multiscale environmental drivers can best be discriminated from a habitat index derived from a remotely sensed vegetation time series?

Understanding which environmental conditions are critical for species survival is a critical, ongoing question in ecology. These conditions can range from climate, at the broadest scale, through to elevation and other local landscape conditions, to fine scale landscape patterns of land cover and use. Remote sensing is an ideal technology to monitor and assess changes in these environmental conditions at a variety of spatial and temporal scales, with many studies focusing on the physiological state of vegetation derived from time series of satellite measurements. As vegetation occurs within specific climatic zones, over certain soil, terrain, and land cover types, it can be difficult to decipher the influence of the underlying role of climate, topography, soil, and land cover on the observed vegetation signal. In this article, we specifically addressed this problem by asking the question: what is the relative impact and importance of these different scales of environmental drivers on the temporal and spatial patterns observed on a habitat index derived from remotely sensed data? To find the solution, we utilized a SPOT VEGETATION-normalized difference vegetation index time series of Europe to create a remote-sensing-derived habitat index, which incorporates aspects of productivity, seasonality, and cover. We then compared the observed temporal and spatial variations in the index to a pan-Europe terrestrial classification system, which explicitly incorporates variations in climate, terrain, soil parent material, land cover, and use. Results indicated that the most accurate level of discrimination from the habitat index was at the broadest level of the hierarchy, climate, while the poorest degree of discrimination was associated with elevation. In terms of similarity on the index across time and space, we found that arable and forest cover classes were more similar across elevation and parent materials than across other land cover types within them. Analyzing the remote-sensing index, at multiple scales, provides significant insights into the drivers of satellite-derived greenness indices, as well as highlights the benefit and cautions associated with linking satellite-derived indirect indicators to species distribution modeling and biodiversity.     

Analysis of fine-scale spatial pattern of a grassland from remotely-sensed imagery and field collected data

An important practical problem in the analysis of spatial pattern in ecological systems is that requires spatially-intensive data, with both fine resolution and large extent. Such information is often difficult to obtain from field-measured variables. Digital imagery can offer a valuable, alternative source of information in the analysis of ecological pattern. In the present paper, we use remotely-sensed imagery to provide a link between field-based information and spatially-explicit modeling of ecological processes. We analyzed one digitized color infrared aerial photograph of a serpentine grassland to develop a detailed digital map of land cover categories (31.24 m × 50.04 m of extent and 135 mm of resolution), and an image of vegetation index (proportional to the amount of green biomass cover in the field). We conducted a variogram analysis of the spatial pattern of both field-measured (microtopography, soil depth) and image-derived (land cover map, vegetation index, gopher disturbance) landscape variables, and used a statistical simulation method to produce random realizations of the image of vegetation index based upon our characterization of its spatial structure. The analysis revealed strong relationships in the spatial distribution of the ecological variables (e.g., gopher mounds and perennial grasses are found primarily on deeper soils) and a non-fractal nested spatial pattern in the distribution of green biomass as measured by the vegetation index. The spatial pattern of the vegetation index was composed of three basic components: an exponential trend from 0 m to 4 m, which is related to local ecological processes, a linear trend at broader scales, which is related to a general change in topography across the study site, and a superimposed periodic structure, which is related to the regular spacing of deeper soils within the study site. Simulations of the image of vegetation index confirmed our interpretation of the variograms. The simulations also illustrated the limits of statistical analysis and interpolations based solely on the semivariogram, because they cannot adequately characterize spatial discontinuities.     

Biodiversity is associated with indicators of soil ecosystem functions over a landscape gradient of agricultural intensification

Agricultural intensification has led to dramatic losses in biodiversity over the past several decades. Many studies have shown the effects of intensification on vegetation or soil communities at field or local scales. However, the functional significance of biodiversity may only appear at larger spatial and temporal scales, due to exchanges among local ecosystems throughout a landscape. To examine how patterns of biodiversity loss are reflected at larger spatial scales, plant and soil biodiversity and associated indicators of ecosystem functions were assessed in riparian areas over a 150 km² agricultural landscape in the Sacramento Valley of California. Publicly-available GIS data were first used to classify and select sites over the range of soils, topography and plant community types. Representative sites from the landscape were sampled for soil physiochemical properties, as well as microbial, nematode, and plant communities. Higher agricultural intensification, based on field and landscape indices, was negatively correlated with richness and diversity of plant and soil taxa, and was related to indicators of ecosystem functions, such as increased soil nitrate and phosphorus loading, decreased riparian health ratings, and lower soil carbon, soil microbial biomass and soil food web structure. Both field- and landscape-scale factors played important roles in the measured losses. The study area was composed of a wide array of soils, vegetation, and land management, indicating that the observed trends transcended site-specific conditions.     

Scaling up ecosystem productivity from patch to landscape: a case study of Changbai Mountain Nature Reserve,China

Scaling up ecosystem processes from plots to landscapes is essential for understanding landscape structure and functioning as well as for assessing ecological impacts of land use and climate change. This study illustrates an upscaling approach to studying the spatiotemporal pattern of ecosystem processes in the Changbai Mountain Nature Reserve in northeastern China by integrating simulation modeling, GIS, remote sensing data, and field-based observations. The ecosystem model incorporated processes of energy transfer, plant physiology, carbon dynamics, and water cycling. Using a direct extrapolation scheme, the patch-level ecosystem model was scaled up to quantify the landscape-level pattern of primary productivity and the carbon source-sink relationship. The simulated net primary productivity (NPP) for the entire landscape, consisting of several ecosystem types, was 0.680 kg C m⁻² yr⁻¹. The most widely distributed ecosystem type in this region was the mixed broad-leaved and Korean pine (Pinus koraiensis) forest, which had the highest NPP (1.084 kg C m⁻² yr⁻¹). The total annual NPP for all ecosystem types combined was estimated to be 1.332 Mt C yr⁻¹. These results suggest that the Changbai Mountain landscape as a whole was a carbon sink, with a net carbon sequestration rate of about 0.884 Mt C yr⁻¹ for the study period. The simulated NPP agreed reasonably well with available field measurements at a number of locations within the study landscape. Our study provides new insight into the relationship between landscape pattern and ecosystem processes, and useful information for improving management practices in the Changbai Mountain Nature Reserve, which is one of the most important forested landscapes in China. Several research needs are discussed to further refine the modeling approach and reduce prediction uncertainties.     

Landscape context and plant community composition in grazed agricultural systems of the Northeastern United States

Temperate humid grazing lands are an important component of the landscape of the northeastern United States, as well as of the economy of this region. Unlike their European counterparts, little is known about the basic ecology of managed grasslands in this region. During an 8-year survey of 28 farms across the northeastern United States, we sampled the vegetation on 95 grazed plots, identifying 310 plant species, and collected data on topography, climate and soils. Landscape structure data were obtained from the National Land Cover Data (NLCD) 2001 for six radii (250–2,000 m) surrounding each site. The 500-m radius was most strongly related to plant community composition. Planned species composition was related only to site factors, while associated species were influenced by both site factors and landscape pattern. Species richness was unrelated to landscape structure for either group. Differing management effects on planned and associated species may explain the variation in their responses. Managed grasslands are a critical part of the interconnected landscape of the northeastern United States, and both affect and are affected by their surroundings.     

阜平县北流河流域林地多功能评价及分区研究

由于人类对土地功能的认识单一,造成乡村地区土地利用不充分,导致土地资源的闲置与浪费。而土地单一功能利用模式转变的关键是探究土地多功能的利用。以北流河流域林地为研究区对象,从气候、土壤、地质、地形、植被要素进行综合分析,对林地土地的生产功能、生态功能、景观功能和材料功能进行空间定量化,运用热点分析和地理探测器评价北流河流域林地多功能性及影响因素;并通过K均值聚类分析划分林地土地多功能利用类型区。结果表明：(1)流域内林地多功能热点区域呈集聚分布,冷点区域呈带状分布在北流河流域的山麓。(2)北流河流域林地多功能空间分异的驱动力主要以植被因素为主,其中郁闭度、蓄积量、碳汇为主导因子,植被盖度对林地土地多功能空间分异的影响较小,应加强北流河流域内的植被保护和严禁过度开发林地;交互作用明显,交互作用均为双因子增强或非线性增强,气候、土壤、植被、地形、地质条件共同制约着北流河流域林地多功能水平。(3)通过伪F统计将北流河流域林地划分为3个主导区和1个提升区,分别为生产功能主导区、生态功能主导区、景观功能主导区以及综合功能提升区,其中生态功能主导区面积最大;并针对主导功能提出相应的利用方向。     

Topography-mediated controls on local vegetation phenology estimated from MODIS vegetation index

Forest canopy phenology is an important constraint on annual water and carbon budgets, and responds to regional interannual climate variation. In steep terrain, there are complex spatial variations in phenology due to topographic influences on microclimate, community composition, and available soil moisture. In this study, we investigate spatial patterns of phenology in humid temperate forest as a function of topography. Moderate-resolution imaging spectro-radiometer (MODIS) vegetation indices are used to derive local patterns of topography-mediated vegetation phenology using a simple post-processing analysis and a non-linear model fitting. Elevation has the most explanatory power for all phenological variables with a strong linear relationship with mid-day of greenup period, following temperatures lapse rates. However, all other phenological variables show quadratic associations with elevation, reflecting an interaction between topoclimatic patterns of temperature and water availability. Radiation proxies also have significant explanatory power for all phenological variables. Though hillslope position cannot be adequately resolved at the MODIS spatial resolution (250 m) to discern impacts of local drainage conditions, extended periods of greenup/senescence are found to occur in wet years. These findings are strongly supported by previous field measurements at different topographic positions within the study area. The capability of detecting topography-mediated local phenology offers the potential to detect vegetation responses to climate change in mountainous terrain. In addition, the large, local variability of meteorological and edaphic conditions in steep terrain provides a unique opportunity to develop an understanding of canopy response to the interaction of climate and landscape conditions.     

Presettlement landscape heterogeneity: Evaluating grain of resolution using General Land Office Survey data

General Land Office Survey (GLOS) records from the A.D. 1840s provide data for quantitative characterization of presettlement vegetation across western Mackinac County, Michigan, located within the mixed conifer-northern hardwoods forest region. We analyzed data from land survey plat maps and 1958 bearing, witness, and line trees from 162 surveyed section and quarter-section corners in order to map vegatation cover types at a level of spatial resolution appropriate for characterizing landscape heterogeneity using standard landscape ecological metrics. As also demonstrated by a number of both classic and contemporary plant-ecological studies, the distribution of landforms, soils properties, hydrology, and location of fire breaks all contribute to the heterogeneity in vegetation observed at a landscape scale in the region. Through a series of spatial landscape analyses with differing grain of resolution, in this study we determine that a grid cell size of 65 ha (0.5 mi×0.5 mi or 0.25 mi²) to 259 ha (1 mi²) gives a conservative characterization of landscape heterogeneity using standard metrics and is therefore appropriate for use of GLOS data to study historical landscape changes.     

Determining landscape extent for succession and disturbance simulation modeling

Dividing regions into manageable landscape units presents special problems in landscape ecology and land management. Ideally, a landscape should be large enough to capture a broad range of vegetation, environmental and disturbance dynamics, but small enough to be useful for focused management objectives. The purpose of this study was to determine the optimal landscape size to summarize ecological processes for two large land areas in the southwestern United States. We used a vegetation and disturbance dynamics model, LANDSUMv4, to simulate a set of nine scenarios involving systematically varied topography, map resolution, and model parameterizations of fire size and fire frequency. Spatial input data were supplied by the LANDscape FIRE Management Planning System (LANDFIRE) prototype project, an effort that will provide comprehensive and scientifically credible mid-scale data to support the National Fire Plan. We analyzed output from 2,000 year simulations to determine the thresholds of landscape condition based on the variability of burned area and dominant vegetation coverage. Results show that optimal landscape extent using burned area variability is approximately 100 km² depending on topography, map resolution, and model parameterization. Variability of dominant vegetation area is generally higher and the optimal landscape sizes are larger in comparison to those features determined from burned area. Using the LANDFIRE project as a case study, we determined landscape size and map resolution for a large mapping project, and showed that optimal landscape size depends upon geographical, ecological, and management context. This paper was written and prepared by U.S. Government employees on official time, and therefore is in the public domain and not subject to copyright. The use of trade or firm names in this paper is for reader information and does not imply endorsement by the U.S. Department of Agriculture of any product or service.     

Landscape pattern in topographically complex landscapes: issues and techniques for analysis

Ecological research provides ample evidence that topography can exert a significant influence on the processes shaping broad-scale landscape vegetation patterns. Studies that ignore this influence run the risk of misinterpreting observations and making inappropriate recommendations to the management community. Unfortunately, the standard methods for landscape pattern analysis are not designed to include topography as a pattern-shaping factor. In this paper, we present a set of techniques designed to incorporate the topographic mosaic into analyses of landscape pattern and dynamics. This toolbox includes adjustments to classic landscape indices that account for non-uniform landscape topography, indices that capture associations and directionality in vegetation pattern due to topographic structure, and the application of statistical models to describe relationships between topographic characteristics and vegetation pattern. To illustrate these methods, we draw on examples from our own analysis of landscape pattern dynamics in logged and unlogged forest landscapes in southwestern British Columbia. These examples also serve to illustrate the importance of considering topography in both research and management applications.This revised version was published online in May 2005 with corrections to the Cover Date.     

The land unit — A fundamental concept in landscape ecology,and its applications

The land unit, as an expression of landscape as a system, is a fundamental concept in landscape ecology. It is an ecologically homogeneous tract of land at the scale at issue. It provides a basis for studying topologic as well as chorologic landscape ecology relationships. A land unit survey aims at mapping such land units. This is done by simultaneously using characteristics of the most obvious (mappable) land attributes: land-form, soil and vegetation (including human alteration of these three). The land unit is the basis of the map legend but may be expressed via these three land attributes. The more dynamic land attributes, such as certain animal populations and water fluxes, are less suitable as diagnostic criteria, but often link units by characteristic information/energy fluxes.The land unit survey is related to a further development of the widely accepted physiographic soil survey see Edelman (1950). Important aspects include: by means of a systems approach, the various land data can be integrated more appropriately; geomorphology, vegetation and soil science support each other during all stages (photo-interpretation, field survey, data processing, final classification); the time and costs are considerably less compared with the execution of separate surveys; the result is directly suitable as a basis for land evaluation; the results can be expressed in separate soil, vegetation, land use and landform maps, or even single value maps.A land unit survey is therefore: a method for efficient survey of land attributes, such as soils, vegetation, landform, expressed in either separate or combined maps; a means of stimulating integration among separate land attribute sciences; an efficient basis for land evaluation. For multidisciplinary projects with applied ecologic aims (e.g., land management), it is therefore the most appropriate survey approach.Within the land unit approach there is considerable freedom in the way in which the various land attribute data are integrated. It is essential, however, that: during the photo-interpretation stage, the contributions of the various specialists are brought together to prepare a preliminary (land unit) photo-interpretation map; the fieldwork data are collected at exactly the same sample point, preferably by a team of specialists in which soil, vegetation and geomorphology are represented; the final map is prepared in close cooperation of all contributing disciplines, based on photo-interpretation and field data; the final map approach may vary from one fully-integrated land unit map to various monothematic maps.     

Upscaling as ecological information transfer: a simple framework with application to Arctic ecosystem carbon exchange

Transferring ecological information across scale often involves spatial aggregation, which alters information content and may bias estimates if the scaling process is nonlinear. Here, a potential solution, the preservation of the information content of fine-scale measurements, is highlighted using modeled net ecosystem exchange (NEE) of an Arctic tundra landscape as an example. The variance of aggregated normalized difference vegetation index (NDVI), measured from an airborne platform, decreased linearly with log(scale), resulting in a linear relationship between log(scale) and the scale-wise modeled NEE estimate. Preserving three units of information, the mean, variance and skewness of fine-scale NDVI observations, resulted in upscaled NEE estimates that deviated less than 4% from the fine-scale estimate. Preserving only the mean and variance resulted in nearly 23% NEE bias, and preserving only the mean resulted in larger error and a change in sign from CO₂ sink to source. Compressing NDVI maps by 70–75% using wavelet thresholding with the Haar and Coiflet basis functions resulted in 13% NEE bias across the study domain. Applying unique scale-dependent transfer functions between NDVI and leaf area index (LAI) decreased, but did not remove, bias in modeled flux in a smaller expanse using handheld NDVI observations. Quantifying the parameters of statistical distributions to preserve ecological information reduces bias when upscaling and makes possible spatial data assimilation to further reduce errors in estimates of ecological processes across scale.     

Landscape-scale controls over 20th century fire occurrence in two large Rocky Mountain (USA) wilderness areas

Topography, vegetation, and climate act together to determine thespatial patterns of fires at landscape scales. Knowledge oflandscape-fire-climate relations at these broad scales (1,000s hato 100,000s ha) is limited and is largely based on inferences andextrapolations from fire histories reconstructed from finer scales. In thisstudy, we used long time series of fire perimeter data (fire atlases) and datafor topography, vegetation, and climate to evaluate relationships between large20^thcentury fires and landscape characteristics in two contrastingareas: the 486,673-ha Gila/Aldo Leopold Wilderness Complex (GALWC)in New Mexico, USA, and the 785,090-ha Selway-BitterrootWilderness Complex (SBWC) in Idaho and Montana, USA. There were importantsimilarities and differences in gradients of topography, vegetation, andclimatefor areas with different fire frequencies, both within and between study areas.These unique and general relationships, when compared between study areas,highlight important characteristics of fire regimes in the Northern andSouthernRocky Mountains of the Western United States.Results suggest that amount and horizontal continuity of herbaceous fuels limitthe frequency and spread of surface fires in the GALWC, while the moisturestatus of large fuels and crown fuels limits the frequency of moderate-to-highseverity fires in the SBWC. These empirically described spatial and temporalrelationships between fire, landscape attributes, and climate increaseunderstanding of interactions among broad-scale ecosystem processes. Resultsalso provide a historical baseline for fire management planning over broadspatial and temporal scales in each wilderness complex.This revised version was published online in May 2005 with corrections to the Cover Date.     

Human appropriated net primary productivity as a metric for land use planning: a case study in the US Great Lakes region

Context

Human appropriation of net primary productivity (HANPP) is employed as a measure of human pressures on biodiversity, though largely at global and national scales rather than landscape to regional scales where many conservation decisions take place. Though gaining in familiarity, HANPP is not widely utilized by conservation professionals.

Objectives

This study, encompassing the US side of the Great Lakes basin, examines how regional distributions of HANPP relate to landscape-based biodiversity proxy metrics used by conservation professionals. Our objectives were (1) to quantify the HANPP of managed lands at the county scale; and (2) to assess spatial patterns of HANPP in comparison to landscape diversity and local habitat connectedness to determine if the metric can provide useful information to conservation professionals.

Methods

We aggregated forest and cropland NPP data between 2005 and 2015 and coupled it with previously published potential vegetation maps to quantify the HANPP of each county in the study region. We mapped the outputs at 500 m resolution to analyze spatial relationships between HANPP and landscape metrics of biodiversity potential.

Results

Area-weighted HANPP across our study region averaged 45% of NPP, down to 4.9% in forest-dominated counties. Greater HANPP correlated with reduced landscape diversity (p?<?0.001, r²?=?0.28) and reduced local habitat connectedness (p?<?0.001, r²?=?0.36).

Conclusion

HANPP could be used as an additional tool for conservation professionals during regional-scale land use planning or conservation decision-making, particularly in mixed-use landscapes that both support important biodiversity and have high levels of primary production harvest.

     

Land Use – Land Cover Conversion, Regeneration and Degradation in the High Elevation Bolivian Andes

Regional land-cover change affects biodiversity, hydrology, and biogeochemical cycles at local, watershed, and landscape scales. Developing countries are experiencing rapid land cover change, but assessment is often restricted by limited financial resources, accessibility, and historical data. The assessment of regional land cover patterns is often the first step in developing conservation and management plans. This study used remotely sensed land cover and topographic data (Landsat and Shuttle Radar Topography Mission), supervised classification techniques, and spectral mixture analysis to characterize current landscape patterns and quantify land cover change from 1985 to 2003 in the Altiplano (2535–4671 m) and Intermediate Valley (Mountain) (1491–4623 m) physiographic zones in the Southeastern Bolivian Andes. Current land cover was mapped into six classes with an overall accuracy of 88% using traditional classification techniques and limited field data. The land cover change analysis showed that extensive deforestation, desertification, and agricultural expansion at a regional scale occurred in the last 20 years (17.3% of the Mountain Zone and 7.2% of the Altiplano). Spectral mixture analysis (SMA) indicated that communal rangeland degradation has also occurred, with increases in soil and non-photosynthetic vegetation fractions in most cover classes. SMA also identified local areas with intensive management activities that are changing differently from the overall region (e.g., localized areas of increased green vegetation). This indicates that actions of local communities, governments, and environmental managers can moderate the potentially severe future changes implied by the results of this study.     

A GIS-based index for relating landscape characteristics to potential nitrogen leaching to wetlands

We developed a spatially-explicit, quantitative Nitrogen Leaching Index to assess the potential for non-point source subsurface nitrogen pollution to wetlands. The index was based on the leaching potential of the watershed soils, the amount of nitrogen available for leaching, and the spatial position of nitrogen sources in the watershed. A raster or cell-based geographic information system (GIS) was used to estimate the necessary data inputs for calculating the index, such as soil hydrologic group, land use/soil type combination, groundwater residence time, and location of septic systems. The Total and Average Watershed Nitrogen Leaching Index (TWNLI and AWNLI) were calculated by summing and averaging, respectively, individual cell contributions over a watershed.Analysis of nine wetland watersheds in central New York state, USA, with mixed forest and agricultural land uses illustrated the use of the index for identifying and ranking wetlands with potential nitrogen pollution. Results showed that the spatial characteristics of a watershed potentially can effect subsurface nitrogen delivery to groundwater-dominated wetlands. The use of an index based on watershed soils, topography, and land use may be useful for assessing potential nitrogen pollution to wetlands at a regional scale.     

The change of a satoyama landscape and its causality in Kamiseya,Kyoto Prefecture,Japan between 1970 and 1995

We focused on patterns of land use in a particular satoyama landscape (Japanese traditional rural landscape, comprised of an integral social and ecological network of a village and its surroundings, such as agricultural lands, open forestlands and forests), and the effects of human activities upon them during Japan’s economic growth of the last few decades. Changes of landscape patterns and their probable causes were traced since the beginning of the 1900s to the present, and clarified. Societal, economic and technological changes, especially those that occurred after 1970, were considered the focal points from which major landscape changes developed. We compared the spatial features, patterns of land use and landscape diversities of each land unit, defined in terms of both their natural and man-made conditions for the year 1970, to those of 1995. We found land-use diversity to be strongly related to changes in the patterns of land use, with a decrease in diversity for all land units after 1970. Diversity of forest-age distribution on the other hand, increased. These changes, with the complex, changing patterns of each land unit, could be explained by differences in accessibility from the village and variations in the topography, as well as land ownership of the land units. We selected those land units found to have responded to these factors between 1970 and 1995, and classified them into four types of pattern changes, determined mainly by accessibility and topography.This revised version was published online in May 2005 with corrections to the Cover Date.     

Additive and synergistic effects of land cover,land use and climate on insect biodiversity

Context

We address the issue of adapting landscapes for improved insect biodiversity conservation in a changing climate by assessing the importance of additive (main) and synergistic (interaction) effects of land cover and land use with climate.

Objectives

We test the hypotheses that ant richness (species and genus), abundance and diversity would vary according to land cover and land use intensity but that these effects would vary according to climate.

Methods

We used a 1000 m elevation gradient in eastern Australia (as a proxy for a climate gradient) and sampled ant biodiversity along this gradient from sites with variable land cover and land use.

Results

Main effects revealed: higher ant richness (species and genus) and diversity with greater native woody plant canopy cover; and lower species richness with higher cultivation and grazing intensity, bare ground and exotic plant groundcover. Interaction effects revealed: both the positive effects of native plant canopy cover on ant species richness and abundance, and the negative effects of exotic plant groundcover on species richness were greatest at sites with warmer and drier climates.

Conclusions

Impacts of climate change on insect biodiversity may be mitigated to some degree through landscape adaptation by increasing woody native vegetation cover and by reducing land use intensity, the cover of exotic vegetation and of bare ground. Evidence of synergistic effects suggests that landscape adaptation may be most effective in areas which are currently warmer and drier, or are projected to become so as a result of climate change.

     

Alternative spatial resolutions and estimation of carbon flux over a managed forest landscape in Western Oregon

Spatially-distributed estimates of biologically-driven CO₂ flux are of interest in relation to understanding the global carbon cycle. Global coverage by satellite sensors offers an opportunity to assess terrestrial carbon (C) flux using a variety of approaches and corresponding spatial resolutions. An important consideration in evaluating the approaches concerns the scale of the spatial heterogeneity in land cover over the domain being studied. In the Pacific Northwest region of the United States, forests are highly fragmented with respect to stand age class and hence C flux. In this study, the effects of spatial resolution on estimates of total annual net primary production (NPP) and net ecosystem production (NEP) for a 96 km² area in the central Cascades Mountains of western Oregon were examined. The scaling approach was a simple `measure and multiply' algorithm. At the highest spatial resolution (25 m), a stand age map derived from Landsat Thematic Mapper imagery provided the area for each of six forest age classes. The products of area for each age class and its respective NPP or NEP were summed for the area wide estimates. In order to evaluate potential errors at coarser resolutions, the stand age map was resampled to grain sizes of 100, 250, 500 and 1000 m using a majority filter reclassification. Local variance in near-infrared (NIR) band digital number at successively coarser grain sizes was also examined to characterize the scale of the heterogeneity in the scene. For this managed forest landscape, proportional estimation error in land cover classification at the coarsest resolution varied from –1.0 to +0.6 depending on the initial representation and the spatial distribution of the age class. The overall accuracy of the 1000 m resolution map was 42% with respect to the 25 m map. Analysis of local variance in NIR digital number suggested a patch size on the order of 100–500 m on a side. Total estimated NPP was 12% lower and total estimated NEP was 4% lower at 1000 m compared to 25 m. Carbon flux estimates based on quantifying differences in total biomass stored on the landscape at two points in time might be affected more strongly by a coarse resolution analysis because the differences among classes in biomass are more extreme than the differences in C flux and because the additional steps in the flux algorithm would contribute to error propagation. Scaling exercises involving reclassification of fine scale imagery over a range of grain sizes may be a useful screening tool for stratifying regions of the terrestrial surface relative to optimizing the spatial resolution for C flux estimation purposes.